Summary:
Due to the growing interest in hybrid nanofluids, researchers were essentially focused to obtain the thermophysical properties of hybrid nanofluids. Several parameters like temperature, volume or weight fractions, nanoparticle types and shapes affected the thermophysical properties of nanofluids. Accordingly, the optimization in thermal conductivity and viscosity of nanofluids obtained by mixing binary nanocomposite particles GnP-Fe3O4 in an ethylene glycol-water base fluid with a mixing ratio of 20-80 % was investigated in this study. The Taguchi approach is used for single-objective optimization and and the significance values of the synthesis parameters were determined using the ANOVA technique. Five different factors, including mechanical strring time, ultrasonic mixing time and power, surfactant mixing ratio, and nanofluid weight ratio, were optimized at three different levels during the synthesis of hybrid nanofluids. The experimental L27 orthogonal array trial was built in order to carry out the optimization. According to the results, mechanical striring time was determined to have the least impact on both thermophysical parameters, whereas ultrasonic mixing power, nanofluid weight ratio, and ultrasonic mixing time were also ranked from low to high impact. The usage of surfactant was shown to be the parameter that had the greatest impact, with rates of 63.57% and 65.31%, on thermal conductivity and viscosity, respectively.